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Whisper tiny TW - AlanDlink
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6078
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.3802 | 0.67 | 500 | 3.3992 |
| 2.1962 | 1.33 | 1000 | 2.1643 |
| 1.4348 | 2.0 | 1500 | 1.4068 |
| 0.7108 | 2.67 | 2000 | 0.6926 |
| 0.6801 | 3.33 | 2500 | 0.6374 |
| 0.6273 | 4.0 | 3000 | 0.6195 |
| 0.6001 | 4.67 | 3500 | 0.6106 |
| 0.6082 | 5.33 | 4000 | 0.6078 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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openai/whisper-tiny